No abstract

The Białowieża Forest (BF), a unique ecosystem of historical significance in central Europe, has a long history of assumed human settlement, with at least 200 known archaeological sites (until 2016). This study uncovers new evidence of the cultural heritage of this unique forest area using Airborne Laser Scanning (ALS) technology combined with traditional archaeological field assessment methods to verify the ALS data interpretations and to provide additional evidence about the function and origin of the newly detected archaeological sites. The results of this study include (1) a scientific approach for an improved identification of archaeological resources in forest areas; (2) new evidence about the history of the human use of the BF based on ALS data, covering the entire Polish part of the BF; and (3) an improved remote sensing infrastructure, supporting existing GIS (Geographic Information System) systems for the BF, a famous UNESCO Heritage site. Our study identified numerous locations with evidence of past human agricultural activities known in the literature as “field systems”, “lynchets” and “Celtic fields”. The initial identification included more than 300 km of possible field boundaries and plough headlands, many of which we have verified on the ground. Various past human activities creating those boundaries have existed since the (pre-) Roman Period up to the 13th century AD. The results of this study demonstrate that past human activities in the Polish part of the Białowieża Forest had been more prevalent than previously believed. As a practical result of the described activities, a geodatabase was created; this has practical applications for the system of monument protection in Poland, as well as for local communities and the BF’s management and conservation. The more widely achieved results are in line with the implementation of the concept of a cultural heritage inventory in forested and protected areas—the actions taken specify (built globally) the forms of protection and management of cultural and environmental goods.

Airborne Laser Scanning (ALS) technology can be used to identify features of terrain relief in forested areas, possibly leading to the discovery of previously unknown archaeological monuments. Spatial interpretation of numerous objects with various shapes and sizes is a difficult challenge for archaeologists. Mapping structures with multiple elements whose area can exceed dozens of hectares, such as ancient agricultural field systems, is very time-consuming. These archaeological sites are composed of a large number of embanked fields, which together form a recognizable spatial pattern. Image classification and segmentation, as well as object recognition, are the most important tasks for deep learning neural networks (DLNN) and therefore they can be used for automatic recognition of archaeological monuments. In this study, a U-Net neural network was implemented to perform semantic segmentation of the ALS-derived data including (1) archaeological, (2) natural and (3) modern features in the Polish part of the Białowieża Forest. The performance of the U-Net segmentation model was evaluated by measuring the pixel-wise similarity between ground truth and predicted segmentation masks. After 83 epochs, The Dice-Sorensen coefficient (F1 score) and the Intersect Over Union (IoU) metrics were 0.58 and 0.5, respectively. The IoU metric reached a value of 0.41, 0.62 and 0.62 for the ancient field system banks, ancient field system plots and burial mounds, respectively. The results of the U-Net deep learning model proved very useful in semantic segmentation of images derived from ALS data.

ABSTRACT. In this paper approaches of historical, archaeological object detection from airborne laser scanning (hereinafter referred to as ASL) data were shown. Presented approach of automatic extraction of potential charcoal pile was the analysis of a selected processing of digital terrain model. In this example, it was attempted to detect archaeological sites on a small test area by usage of template matching. Positive results have proved a great number of detected objects. Methodology applied in the research allowed for finding of a large percentage of measured objects indirectly. Presented approach was also assessed by the results of object extraction in respect to field measurements in the area of interest, as well as effectiveness of automation procedure.

This article presents the results and potential of using volunteered geographic information (VGI) in heritage detection. Research was completed under the project entitled “Laser Discoverers – non‐invasive examination and documentation of archeological and historical objects in the Świętokrzyskie Voivodeship”, carried out as a part of the Ministry of Science and Higher Education program entitled “The Paths of Copernicus”. Within the project, strong emphasis was placed on promotional and awareness‐raising activities, to involve as many voluntary users as possible. Project participants had at their disposal a web application, which provided access to a digital terrain model (DTM) where they identified possible heritage objects. All samples of data were additionally available in eight variants of sunshine, based on the simulation of sunlight from eight directions and at a constant angle. In total, 5,989 elementary areas with dimensions of 100 × 100 m were used for the project. After conducting a field inventory, Internet users together with specialists were able to recognize several thousands of potential archaeological and historic objects. During the project, approximately 10% of those features were verified through non‐invasive (field survey) work, with 75% success.